Evidence of Gender Differences in the Diagnosis and Management of Coronavirus Disease 2019 Patients: An Analysis of Electronic Health Records Using Natural Language Processing and Machine Learning
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SciScore for 10.1101/2020.07.20.20157735: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: 15 This study was classified as a ‘non-post-authorization study’ (EPA) by the Spanish Agency of Medicines and Health Products (AEMPS), and was approved by the Research Ethics Committee at the University Hospital of Guadalajara (Spain).
Consent: Given that clinical information was handled in an aggregate, anonymized, and irreversibly dissociated manner, patient consent regulations do not apply to the present study.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable To test for possible statistically significant differences in the distribution of categorical variables between males and females, we used … SciScore for 10.1101/2020.07.20.20157735: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: 15 This study was classified as a ‘non-post-authorization study’ (EPA) by the Spanish Agency of Medicines and Health Products (AEMPS), and was approved by the Research Ethics Committee at the University Hospital of Guadalajara (Spain).
Consent: Given that clinical information was handled in an aggregate, anonymized, and irreversibly dissociated manner, patient consent regulations do not apply to the present study.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable To test for possible statistically significant differences in the distribution of categorical variables between males and females, we used Yates-corrected chi2 tests for percentages or analysis of variance for normally distributed continuous variables. Table 2: Resources
Software and Algorithms Sentences Resources 16 Study design, data source, and patient population: This was a retrospective, multicenter study using secondary free-text data from patients’ EHRs within the SESCAM Healthcare Network in Castilla-La Mancha, Spain. SESCAM Healthcaresuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: The main strengths of our research include immediacy, large sample size, and direct access to real-world evidence (RWE). Of note, our methodology ensures absence of any bias in patient selection as our hypothesis that gender impacts diagnosis and management of COVID-19 was assessed a posteriori. The observed change in the sex ratio of confirmed cases at the tail of this first wave of the pandemic should be further confirmed in other cohorts and geographical locations.33 Finally, it is unlikely that our conclusions are impacted by the limitations of pay- or copay-systems, as Spain enjoys an universal, free-for-all health care system. Our results should be interpreted in light of the following limitations. First, given the variation in COVID-19 severity, it is possible that the free-text information available in EHRs is not homogeneous across patients seen in different points of care (i.e., primary-to-tertiary care). For instance, care providers could have been more likely to further explore (and report more often) milder symptoms in women, who in turn are more likely to be seen in primary care; on the other hand, the more sever ymptoms reported in men may be related to the fact that they were more likely to be hospitalized or visit the ICU. Second, it is possible that women were more likely than men to report ENT symptoms.34 Third, as indicated in the methods section, our reported COVID-19 prevalence rates are probably lower than real, as some cases ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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